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Computational Stochastic Programming Models, Algorithms, and Implementation

This book provides a foundation in stochastic, linear, and mixed-integer programming algorithms with a focus on practical computer algorithm implementation. The purpose of this book is to provide a foundational and thorough treatment of the subject with a focus on models and algorithms and their com...

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Bibliographic Details
Main Author: Ntaimo, Lewis
Format: eBook
Language:English
Published: Cham Springer International Publishing 2024, 2024
Edition:1st ed. 2024
Series:Springer Optimization and Its Applications
Subjects:
Computer Science / Mathematics
Dynamical Systems
Algorithms
Calculus Of Variations And Optimization
Mathematical Models Of Cognitive Processes And Neural Networks
Probability Theory
Mathematical Applications In Computer Science
Neural Networks (computer Science) 
Mathematical Optimization
Calculus Of Variations
Probabilities
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 1. Introduction
  • 2 Stochastic Programming Models
  • 3 Modeling and Illustrative Numerical Examples
  • 4 Example Applications of Stochastic Programming
  • 5 Deterministic Large-Scale Decomposition Methods
  • 6 Risk-Neutral Stochastic Linear Programming Methods
  • 7 Mean-Risk Stochastic Linear Programming Methods
  • 8 Sampling-Based Stochastic Linear Programming Methods
  • 9 Stochastic Mixed-Integer Programming Methods
  • 10 Computational Experimentation.

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